An analytical and machine learning approach to evaluating economic impacts of digital transformation

Digital transformation has become a significant driver of economic and social development in the twenty-first century, producing both positive and negative economic repercussions. It involves the strategic integration of digital technologies, including artificial intelligence (AI), cloud computing, and the Internet of Things (IoT), across business, government, and societal functions to transform operations, enhance value creation, improve adaptability, and support long-term sustainability. This study examines the relationship between digital transformation, AI-driven technological development, economic repercussions, and technology-bubble dynamics. Key findings: AI and digital transformation have emerged as important concerns for economists, policymakers, and technology-driven organizations. Generative AI is increasingly evolving from an emerging technology into a strategic tool for decision-making, while effective data strategies have become central to successful digital transformation. In developing economies, digital transformation provides opportunities to address developmental barriers, industrialization challenges, poverty, educational inequalities, and limited healthcare access. However, the shortage of skilled professionals capable of implementing and managing advanced technologies remains a significant challenge. Methods: This study reviews and comparatively analyses machine learning, deep learning, and advanced analytical methods used to evaluate economic repercussions associated with digital transformation. The analysis considers computational cost, time complexity, efficiency, economic outcomes, investment behaviour, and technology-related risks. Particular attention is given to the evolution of technology bubbles, including Tech Bubble 1.0 (Dot-Com), Tech Bubble 2.0 (Post-2008/COVID-19), and Tech Bubble 3.0 (AI and emerging technologies). Conclusion: Digital transformation is not a one-time technological initiative but a continuous process of organizational and economic adaptation. The study identifies major developments, methodological trends, economic implications, opportunities, challenges, and potential technology-bubble risks, providing insights into sustainable digital transformation and future AI-driven economic development.